Next-hop Selection Research Articles

An Efficient Geo-Routing-Aware MAC Protocol Based on OFDM for Underwater Acoustic Networks

Performing an effective Media Access Control (MAC) protocol suffers from strong dependencies between Underwater Acoustic Networks’ upper and lower layers: 1) the network layer frequently uses geo-routing protocols, which do not provide the specific next-hop for MAC protocols, resulting in serious data collisions. 2) in such scenarios with the unknown next-hop, fixed Orthogonal Frequency Division Multiplexing (OFDM) resource does not adapt to the changing environment, and degrades network performance (OFDM is a mature modulation technology in the physical layer). However, there is scant research on MAC protocols considering the network layer and the physical layer simultaneously, to solve data collisions and resource allocation. To this end, we present a cross-layer MAC protocol to integrate Geo-routing protocols and OFDM technology (GO-MAC) at the same time. GO-MAC employs a handshake scheme to allocate optimal communication resources and select the next-hop concurrently. Firstly, we formulate the OFDM resource allocation as a joint optimization problem based on transmission mode, subcarrier spacing, guard interval, and transmission power, to decrease transmission delay and energy consumption. Then a Karush-Kuhn-Tucker conditions based Heuristic algorithm (KKT-H) is proposed to solve this problem. Finally, we consider node congestion and channel quality to assist geo-routing protocols with the next-hop selection, and decrease packet collisions. Simulation results show that our protocol matches geo-routing protocols and OFDM technology better than the state-of-the-art protocols, providing higher end-to-end reliability with lower costs.

Double Q-learning based routing protocol for opportunistic networks

Opportunistic Delay Tolerant Networks also referred to as Opportunistic Networks (OppNets) are a subset of wireless networks having mobile nodes with discontinuous opportunistic connections. As such, developing a performant routing protocol in such an environment remains a challenge. Most research in the literature have shown that reinforcement learning-based routing algorithms can achieve a good routing performance, but these algorithms suffer from under-estimations and/or over-estimations. Toward addressing these shortcomings, in this paper, a Double Q-learning based routing protocol for Opportunistic Networks framework named Off-Policy Reinforcement-based Adaptive Learning (ORAL) is proposed, which selects the most suitable next-hop node to transmit the message toward its destination without any bias by using a weighted double Q-estimator. In the next-hop selection process, a probability-based reward mechanism is involved, which considers the node’s delivery probability and the frequency of encounters among the nodes to boost the protocol’s efficiency. Simulation results convey that the proposed ORAL protocol improves the message delivery ratio by maintaining a trade-off between underestimation and overestimation. Simulations are conducted using the HAGGLE INFOCOM 2006 real mobility data trace and synthetic model, showing that when time-to-live is varied, (1) the proposed ORAL scheme outperforms DQLR by 14.05%, 9.4%, 5.81% respectively in terms of delivery probability, overhead ratio and average delay; (2) it also outperforms RLPRoPHET by 16.17%, 9.2%, 6.85%, respectively in terms of delivery ratio, overhead ratio and average delay.

Improved Multi-Path Routing for QoS on MANET

A Mobile Ad hoc NETwork (MANET) is a self-configuring network that is not reliant on infrastructure. This paper introduces a new multipath routing method based on the Multi-Hop Routing (MHR) technique. MHR is the consecutive selection of suitable relay nodes to send information across nodes that are not within direct range of each other. Failing to ensure good MHR leads to several negative consequences, ultimately causing unsuccessful data transmission in a MANET. This research work consists of three portions. The first to attempt to propose an efficient MHR protocol is the design of Priority Based Dynamic Routing (PBDR) to adapt to the dynamic MANET environment by reducing Node Link Failures (NLF) in the network. This is achieved by dynamically considering a node’s mobility parameters like relative velocity and link duration, which enable the next-hop selection. This method works more efficiently than the traditional protocols. Then the second stage is the Improved Multi-Path Dynamic Routing (IMPDR). The enhancement is mainly focused on further improving the Quality of Service (QoS) in MANETs by introducing a QoS timer at every node to help in the QoS routing of MANETs. Since QoS is the most vital metric that assesses a protocol, its dynamic estimation has improved network performance considerably. This method uses distance, linkability, trust, and QoS as the four parameters for the next-hop selection. IMPDR is compared against traditional routing protocols. The Network Simulator-2 (NS2) is used to conduct a simulation analysis of the protocols under consideration. The proposed tests are assessed for the Packet Delivery Ratio (PDR), Packet Loss Rate (PLR), End-to-End Delay (EED), and Network Throughput (NT).

A Generalized Framework for Joint Dynamic Optimal RF Interface Setting and Next-Hop Selection in IoT Networks With Similar Requests

Many applications which run on the Internet-of-Things machines require similar bandwidths. These machines are equipped with multiple Radio Frequency (RF) interfaces for machine-to-machine or machine-to-Base Station(BS) communications. Joint dynamic optimal RF interface setting and next-hop selection in data transmission can maximize the network data rate. For this purpose, we propose a generalized framework for simultaneous selection of these components according to the required bandwidth of machines. This framework is suitable for networks with multiple BSs and sources with similar bandwidth requests. Simulation results show that using the proposed framework, the average data rate of network sources increases up to 117%.

3D Void Handling Geographic P2P-RPL for Indoor Multi-Hop IR-UWB Networks

IETF has standardized the point-to-point RPL (P2P-RPL) to ensure reliable and optimal P2P route discovery for low-power and lossy networks (LLNs). P2P-RPL propagates route discovery packets to all nodes in the network, which results in high routing communication overheads. Recently, other RPL-based P2P routing algorithms have been proposed to reduce such overheads, but still, quite an amount of overheads occur due to their flooding-based approach. In real life 3D environments, a larger number of nodes should be deployed to guarantee the full network connectivity, and thus the flooding strategy incurs higher overheads. In effort to alleviate high overheads, geographic routing is an attractive solution that exploits the nodes’ geographic locations in its next-hop routing selection. However, geographic routing inherently suffers from the local minimum (void) problem following greedy next-hop selection. Local minima occur more often in 3D space, and therefore, a reliable 3D void handling technique is required. In this paper, we propose greedy forwarding and void handling point-to-point RPL with adaptive trickle timer (GVA-P2P-RPL), which is a novel RPL-based P2P routing protocol that quickly discovers energy-efficient and reliable P2P routes in 3D networks. In GVA-P2P-RPL, P2P-RPL is modified to greedily forward routing packets when it is possible. IR-UWB-based 3D multi-hop self-positioning is conducted in advance to obtain the geographical location of each node. When local minima are encountered, routing packets are temporarily broadcast just like in the traditional P2P-RPL. A new trickle algorithm called adaptive trickle timer (ATT) is also presented to reduce route discovery time and provide better collision avoidance effects. The performance of GVA-P2P-RPL is compared with that of P2P-RPL, partial flooding-based P2P-RPL (PF-P2P-RPL) and ER-RPL. It shows significant improvements in route discovery overheads and route discovery time against these state-of-the-art RPL-based P2P routing methods in 3D environments. Performance evaluation in the special network case where a huge 3D void volume exists in the center is also presented to show the strong void recovery capability of the proposed GVA-P2P-RPL in 3D environments.

Efficient Next-Hop Selection in Multi-Hop Routing for IoT Enabled Wireless Sensor Networks

The Internet of Things (IoT) paradigm allows the integration of cyber and physical worlds and other emerging technologies. IoT-enabled wireless sensor networks (WSNs) are rapidly gaining interest due to their ability to aggregate sensing data and transmit it towards the central or intermediate repositories, such as computational clouds and fogs. This paper presents an efficient multi-hop routing protocol (EMRP) for efficient data dissemination in IoT-enabled WSNs where hierarchy-based energy-efficient routing is involved. It considers a rank-based next-hop selection mechanism. For each device, it considers the residual energy to choose the route for data exchange. We extracted the residual energy at each node and evaluated it based on the connection degree to validate the maximum rank. It allowed us to identify the time slots for measuring the lifetime of the network. We also considered the battery expiry time of the first node to identify the network expiry time. We validated our work through extensive simulations using Network Simulator. We also implemented TCL scripts and C language code to configure low-power sensing devices, cluster heads and sink nodes. We extracted results from the trace files by utilizing AWK scripts. Results demonstrate that the proposed EMRP outperforms the existing related schemes in terms of the average lifetime, packet delivery ratio, time-slots, communication lost, communication area, first node expiry, number of alive nodes and residual energy.

Greedy Load Balancing Energy Efficient Routing Scheme for Wireless Sensor Networks

Background: Despite so many constraints, the limited battery power of the sensor nodes is the core issue in Wireless Sensor Networks. This compels how to extend the lifetime of the network as long as possible. One of the ways to solve the problem is to balance the relay traffic load to extend the lifetime. Objective: In this paper, a load balancing algorithm is suggested that selects the best possible relay node so that uniform consumption of the battery power of the sensor nodes can be ensured. Methods: After random deployment, sensor nodes collect information about their neighbors and their expected load. The selection of new next hop starts from maximum hop count. Next hop of the nodes having a single parent is set first. Remaining nodes select their next hop in the non-increasing order of their load. Results: Simulation results verify that packet delivery ratio for proposed work is up to 50% till 72% of total time duration and no nodes getting dead till 48% of total time duration, while for others, nodes start getting dead around 36% of total time duration. Also, it is proved that the solution obtained by proposed work can be at most 1.5 times imbalanced as compared to the optimal solution which implies our solution is quite near to the optimal one. Conclusion: Load balancing done in our work has shown more positive results in comparison to others in terms of network lifetime and first node death and which is also verified with F-test with α- value to be 0.05.

A wireless weak-connected network routing algorithm inspired by Physarum polycephalum

Wireless weak-connected network (WWN) is a special self-organizing network, which can self-organize in an unstructured style and communicate with each other without infrastructure support. In this network, the link connection is weak and the topology is dynamic, which limits the performance of routing tasks. In order to address this issue, a novel Physarum-inspired routing algorithm (P-iRA) is proposed based on the intelligence and adaptability of Physarum polycephalum. Firstly, we construct a link capacity model for WWN via mapping the Physarum polycephalum network. Then, we design a next-hop selection strategy to obtain an optimal forwarding node in candidate set. Finally, we present a stochastic route strategy to achieve data transmission by virtue of finding the best routing path. Simulation results demonstrate that P-iRA improves approximately 47%, 34%, 56%, 20%, and 8% compared with Direct Delivery, Epidemic, First Contact, MaxProp, and Spray And Wait, respectively.

A geographic routing protocol based on trunk line in VANETs

A Trunk Line Based Geographic Routing(TLBGR) protocol in Vehicular Ad-hoc Networks (VANETs) is proposed in this paper to solve the problem of data acquisition in the traditional trunk coordinated control system. Because of the characteristics of short communication time and high packet loss among vehicles, the vehicles entering the trunk lines can not transmit their information to the trunk coordinated control system stably. To resolve this problem, the proposed protocol uses the trunk lines’ traffic flow and the surrounding road network to provide a real-time data transmission routing scheme. It takes into account the data congestion problem caused by the large traffic flow of the main roads, which leads to the corresponding increase of the information flow of the section and the package loss, and the link partition problem caused by the insufficient traffic flow, which makes the vehicles have to carry and relay information thus increasing the transmission delay. The proposed TLBGR protocol can be divided into two stages: the next-intersection selection, and the next-hop selection in the chosen path between the current and next intersections. Simulation results show that, compared with other IoT routing protocols including Greedy Perimeter Stateless Routing (GPSR), Ad-hoc On Demand Vector (AODV), and Q-AODV, the TLBGR protocol has better performance in aspects of end-to-end delay, delivery rate, and routing cost under the scenario of urban traffic trunk lines. The TLBGR protocol can effectively avoid data congestion and local optimum problems, increase the delivery rate of data packets, and is therefore suitable for the routing requirements in this application scenario.

IoT Enabled Cluster Based Energy Aware Routing Protocol In WSN

Because of the unpredictable nature of sensor nodes, propagating sensory data raises significant research challenges in Wireless Sensor Networks (WSNs). Recently, different cluster-based solutions are designed to improve network stability and lifetime. However, most energy-efficient solutions are developed for homogeneous networks and uses only a distance parameter for data communication. Although, some existing solutions are attempted to improve the selection of next-hop based energy factor. Nevertheless, such solutions are unstable and lack reduce data delivery interruption in overloaded links. Our proposed solution aims to develop Reliable Cluster-based Energy-aware Routing (RCER) protocol for heterogeneous WSN which lengthens network lifetime and decreases routing cost. Our proposed RCER protocol makes use of heterogeneity nodes concerning their energy and comprises of two main phases; firstly, the network field is parted in geographical clusters to make the network more energy-efficient and secondly; RCER attempts optimum routing for improving the next-hop selection by considering residual-energy, hop-count and weighted value of Round-Trip Time (RTT) factors. Moreover, RCER restores routing paths and provides network reliability with improved data delivery performance. Simulation results demonstrate significant development of RCER protocol against their competing solutions.

Comparative Study of Energy Efficient Routing Techniques in Wireless Sensor Networks

This paper surveys the energy-efficient routing protocols in wireless sensor networks (WSNs). It provides a classification and comparison following a new proposed taxonomy distinguishing nine categories of protocols, namely: Latency-aware and energy-efficient routing, next-hop selection, network architecture, initiator of communication, network topology, protocol operation, delivery mode, path establishment and application type. We analyze each class, discuss its representative routing protocols (mechanisms, advantages, disadvantages…) and compare them based on different parameters under the appropriate class. Simulation results of LEACH, Mod-LEACH, iLEACH, E-DEEC, multichain-PEGASIS and M-GEAR protocols, conducted under the NS3 simulator, show that the routing task must be based on various intelligent techniques to enhance the network lifespan and guarantee better coverage of the sensing area.

Delay aware energy-efficient opportunistic node selection in restricted routing

Mobile sink can implicitly provide uniform energy consumption across sensor networks and load-balanced data delivery by alleviating the sensor data disruptions and hotspot problems. Advertisement of mobile sink's current position in ring routing introduces control packet overhead in terms of energy consumption and leads to shorter network lifetime. In order to minimize this overhead, we have exploited the functionality of ring nodes rather than anchor nodes for the advertisement of mobile sink's current position and forwarding the aggregated data towards mobile sink. In this paper, we propose a novel, distributed, Delay Aware and Energy-Efficient Opportunistic Node Selection in Restricted Routing (DA-EEORR) protocol, suitable for delay-sensitive applications. Based on asynchronous working-sleeping cycle of sensor nodes, our proposed scheme utilizes the concept of opportunistic connection random graph in ring routing for selection of next-hop using optimal link and path connectivity in restricted search space. Our simulation results reveal that proposed scheme outperforms the existing benchmarks i.e., hierarchical mobile sink routing schemes in terms of control packet overhead, network lifetime, energy consumption and packet delivery ratio.

Energy and spectrum aware unequal clustering with deep learning based primary user classification in cognitive radio sensor networks

The problem of energy efficiency in cognitive radio sensor networks (CRSN) is mainly caused by the limited energy of sensor nodes and other channel-related operations for data transmission. The unequal clustering method should be considered for balancing the energy consumption among the cluster heads (CHs) for prolonging the network lifetime. The CH selection should consider the number of accessible free channels for efficient channel assignment. To improve fairness, the channel assignment problem should consider energy consumption among the cluster members. Furthermore, the relay metric for the selection of the best next-hop should consider the stability of the link for improving the transmission time. The CH rotation for cluster maintenance should be energy and spectrum aware. With regard to the above objectives, this paper proposes an energy and spectrum aware unequal clustering (ESAUC) protocol that jointly overcomes the limitations of energy and spectrum for maximizing the lifetime of CRSN. Our proposed ESAUC protocol improves fairness by achieving residual energy balance among the sensor nodes and enhances the network lifetime by reducing the overall energy consumption. Deep Belief Networks algorithm is exploited to predict the spectrum holes. ESAUC improves the stability of the cluster by optimally adjusting the number of common channels. ESAUC uses a CogAODV based routing mechanism to perform inter-cluster forwarding. Simulation results show that the proposed scheme outperforms the existing CRSN clustering algorithms in terms of residual energy, Network Lifetime, secondary user–primary user Interference Ratio, Route Discovery Frequency, throughput, Packet Delivery Ratio, and end-to-end delay.

A Distributed Survivable Routing Algorithm for Mega-Constellations With Inclined Orbits

Mega-constellations consisting of hundreds to thousands of low-earth-orbit (LEO) satellites are an attractive solution for providing global ubiquitous network access. Due to good coverage properties for populated areas, inclined orbits are gaining popularity among commercial constellations. A scalable routing algorithm with survivability plays a key role in such systems. In this paper, we propose a distributed survivable routing algorithm for mega-constellations with inclined orbits. First, the special topology characteristic of inclined constellations is identified and formalized. Based on the topology characterization, a basic X-Y routing algorithm is presented to determine multiple primary and secondary paths towards each destination utilizing the regularity of the network topology with minimal computation overhead. Then, a failure recovery mechanism which consists of a restricted flooding mechanism and a pre-detour mechanism is proposed to reduce end-to-end delay and signaling overhead in case of link failures. Besides, a partial-record loop avoidance mechanism is proposed to deal with routing loops with minimal overhead. Finally, a vector-based next hop selection mechanism is proposed to facilitate the selection of next hop while incorporating various criteria. The performance of the proposed routing algorithm is evaluated through simulation on the Starlink constellation. Simulation results show that our proposal achieves scalability by reducing signaling overhead and provides better quality of service in terms of end-to-end delay under link failures.

A Routing Model Based on Multiple-User Requirements and the Optimal Solution

To promote the development of high-bandwidth IP networks of nongeostationary Earth orbit (NGEO) satellites, this article designs a new benefit measurement model. Moreover, we propose the class-A QoS benefit criterion (QABC), which is established based on a mathematical model involving the remaining queue length and QoS. The benefit model includes three maximum and minimum conflict subgoals and is designed to avoid the problem that the ant colony algorithm easily falls to local optima. This new model is solved with the wolf colony algorithm, which provides both next-hop selection and bottleneck bandwidth reservation mechanisms. Additionally, many burst flows can occur in satellite networks, and they lead to a slow convergence speed and unnecessary overhead. In this article, the Kalman filter algorithm is used to address these issues. Considering the long-term correlation of satellite traffic, it is feasible to smooth the queue length with a Kalman filter. Finally, the Kalman filter wolf colony algorithm (KFWCA) can solve the conflict problem in the new benefit measurement model. The algorithm is applied in the network simulator NS2.35, and the results verify the effectiveness of load balancing and QoS maximization in a satellite network. The results indicate that the KFWCA yields better performance than other algorithms based on traffic allocation, the average delay, the packet loss rate and other factors, especially under high-traffic conditions.

RCER: Reliable Cluster-based Energy-aware Routing protocol for heterogeneous Wireless Sensor Networks.

Nowadays, because of the unpredictable nature of sensor nodes, propagating sensory data raises significant research challenges in Wireless Sensor Networks (WSNs). Recently, different cluster-based solutions are designed for the improvement of network stability and lifetime, however, most of the energy efficient solutions are developed for homogeneous networks, and use only a distance parameter for the data communication. Although, some existing solutions attempted to improve the selection of next-hop based on energy factor, nevertheless, such solutions are unstable and lack a reducing data delivery interruption in overloaded links. The aim of our proposed solution is to develop Reliable Cluster-based Energy-aware Routing (RCER) protocol for heterogeneous WSN, which lengthen network lifetime and decreases routing cost. Our proposed RCER protocol make use of heterogeneity nodes with respect to their energy and comprises of two main phases; firstly, the network field is parted in geographical clusters to make the network more energy-efficient and secondly; RCER attempts optimum routing for improving the next-hop selection by considering residual-energy, hop-count and weighted value of Round Trip Time (RTT) factors. Moreover, based on computing the measurement of wireless links and nodes status, RCER restore routing paths and provides network reliability with improved data delivery performance. Simulation results demonstrate significant development of RCER protocol against their competing solutions.

Pareto set based optimized routing in opportunistic network

In opportunistic networks (OppNets), messages are transmitted between nodes in an opportunistic fashion following a store-carry-and-forward approach and a routing protocol, with the hope to reach their destinations. In existing routing protocols for OppNets, different parameters such node’s delivery predictability, node’s mobility, distance with respect to destination, node’s energy consumption, contact duration between nodes, to name a few, are considered in the selection of the best suitable next hop to carry the message toward the destination. This paper proposes a novel routing protocol that uses three parameters, namely the contact duration, the node’s residual energy and the signal- to-noise-plus-interference-ratio (SINR) simultaneously to decide on the selection of the best next forwarder for a message. Simulation results using the Opportunistic Network Environment (ONE) simulator are presented, demonstrating the effectiveness of the proposed technique.

A priority-based congestion-avoidance routing protocol using IoT-based heterogeneous medical sensors for energy efficiency in healthcare wireless body area networks

A wireless body area network is a collection of Internet of Things–based wearable heterogeneous computing devices primarily used in healthcare monitoring applications. A lot of research is in process to reduce the cost and increase efficiency in medical industry. Low power sensor nodes are often attached to high-risk patients for real-time remote monitoring. These sensors have limited resources such as storage capacity, battery life, computational power, and channel bandwidth. The current work proposes a multi-hop Priority-based Congestion-avoidance Routing Protocol using IoT based heterogeneous sensors for energy efficiency in wireless body area networks. The objective is to devise a routing protocol among sensor nodes such that it has minimum delay and higher throughput for emergency packets using IoT based sensor nodes, optimal energy consumption for longer network lifetime, and efficient scarce resource utilization. In our proposed work, data traffic is categorized into normal and emergency or life-critical data. For normal data traffic, next-hop selection will be selected based upon three parameters; residual energy, congestion on forwarder node, and signal-to-noise ratio of the path between source and forwarder node. We use the data aggregation and filtration technique to reduce the network traffic load and energy consumption. A priority-based routing scheme is also proposed for life-critical data to have less delay and greater throughput in emergency situations. Performance of the proposed protocol is evaluated with two cutting-edge routing techniques iM-SIMPLE and Optimized Cost Effective and Energy Efficient Routing. The proposed model outperforms in terms of network throughput, traffic load, energy consumption, and lifespan.

Connectedness-Aware Copy-Adaptive Routing Protocol in Intermittently Connected Networks

In the intermittently connected networks where the complete paths from a source to a destination do not always exist, multi-copy forwarding is considered to be capable of providing more reliable transmission than single-copy forwarding. However, injecting too many copies into a network can cause unnecessary network resource consumption that degrades the network performance, especially if the network nodes are low-cost and resource-constrained. Therefore, copy control is a critical efficiency mechanism for the forwarding protocols in such situations. Using a preset threshold is a common copy-control mechanism used by many multi-copy forwarding protocols. The preset threshold is the maximum allowed number of copies of a packet in a network, calculated before running these protocols. It can effectively reduce the unnecessary copies and provide better performance than the protocols without using copy control. However, preset threshold makes the protocol less flexible with respect to the variations of network characteristics such as density or connectedness caused by node failures or new nodes joining. In this paper, we propose a multi-copy routing algorithm, Connectedness-Aware Copy-Adaptive Routing (CACAR) protocol, which adopts a novel copy-control mechanism. CACAR estimates the network connectedness locally and conducts the copy control and the next-hop selection based on the measured connectedness. This proposed protocol can achieve a higher delivery rate and lower latency without sacrificing the energy efficiency compared with other benchmark multi-copy routing protocols.

A multi-hop routing protocol for video transmission in IoVs based on cellular attractor selection

Video transmission in Internet of Vehicles (IoVs) is an emerging technology which utilizes the multimedia inside and outside vehicles itself through Vehicle Ad Hoc Networks (VANETs). In IoVs, traditional multi-hop routing protocols are not adaptive to mobile environment, especially the high-mobility driving environment in which vehicles need to accomplish video transmission under high quality of service (QoS). In this paper, we propose a multi-hop routing protocol for video transmission in IoVs based on cellular attractor selection (MRVT-CAS). We design a packet generation method for MRVT-CAS and use Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to construct the candidate set of next-hop selection. Then we map the expression of different genes in cell to selection of different next-hop nodes, and employ the mechanics of cellular attractor selection to select next-hop node. Moreover, we present a real-time feedback process to improve self-adaptability and robustness of routing protocol. Our simulation study compares MRVT-CAS with other routing protocols to evaluate performance of video transmission. The simulation results demonstrate the performance improvement over traditional methods, in terms of reachability, delay, stability and frame loss rate.